Abstract: An ultrasound guidance dynamic progression method includes selecting a predetermined ultrasound diagnostic workflow in memory of an ultrasound diagnostic computing system, the workflow including a sequence of views of a target organ. The method further includes selecting a first view in the sequence and presenting guidance in a display of the computing system for the first view, for instance visual, audible or haptic feedback. The method yet further includes acquiring imagery in the computing system in association with the first view, and detecting an anomalous feature of the acquired imagery. Finally, the method includes selecting a different view in the sequence as a substitute for a next one of the views in the sequence in response to having detected the anomalous feature, and further presenting different guidance in the display for the different view in lieu of guidance for the next one of the views.

Abstract: Embodiments of the present invention provide a method, system and computer program product for ultrasound image acquisition optimization according to different respiration modes. A method for ultrasound image acquisition optimization according to different respiration modes includes acquiring by an ultrasound imaging device, an ultrasound image of a target organ. The method further includes comparing attributes of the acquired ultrasound image to association data in a data store of associations associating attributes of previously acquired ultrasound imagery of different images of the target organ with different modes of respiration. Finally, the method includes determining from the comparison, a mode of respiration evident from the acquired ultrasound image and presenting the determined mode in the ultrasound imaging device.

Abstract: An automatic extraction of disease-specific features from Doppler images to help diagnose valvular diseases is provided. The method includes the steps of obtaining a raw Doppler image from a series of images of an echocardiogram, isolating a region of interest from the raw Doppler image, the region of interest including a Doppler image and an ECG signal, and depicting at least one heart cycle, determining a velocity envelope of the Doppler image in the region of interest, extracting the ECG signal to synchronize the ECG signal with the Doppler image over the at least one heart cycle, within the region of interest, calculating a value of a clinical feature based on the extracted ECG signal synchronized with the velocity envelope, and comparing the value of the clinical feature with clinical guidelines associated with the clinical feature to determine a diagnosis of a disease.

Abstract: The continuous and dynamic computation of ejection fraction (EF) includes training a neural network with different sets of cardiac imaging data acquired of a ventricle for different hearts and a known EF for each of the sets and then loading the trained neural network into memory of a computer. Afterwards, contemporaneous sets of imaging data of a ventricle of a heart are continuously acquired according to a specified view. For each corresponding set of imaging data, an image quality value may then be computed, and the corresponding set of imaging data may be provided to the neural network. The neural network, in response, provides, as output, an EF determination output without tracing a ventricle boundary of the heart. Thereafter, both the computed image quality value and the EF determination output may be displayed in a display of the computer.

Abstract: Embodiments of the present invention provide a method, system and computer program product for ultrasound image acquisition optimization according to different respiration modes. A method for ultrasound image acquisition optimization according to different respiration modes includes acquiring by an ultrasound imaging device, an ultrasound image of a target organ. The method further includes comparing attributes of the acquired ultrasound image to association data in a data store of associations associating attributes of previously acquired ultrasound imagery of different images of the target organ with different modes of respiration. Finally, the method includes determining from the comparison, a mode of respiration evident from the acquired ultrasound image and presenting the determined mode in the ultrasound imaging device.

Abstract: An ultrasound guidance dynamic progression method includes selecting a predetermined ultrasound diagnostic workflow in memory of an ultrasound diagnostic computing system, the workflow including a sequence of views of a target organ. The method further includes selecting a first view in the sequence and presenting guidance in a display of the computing system for the first view, for instance visual, audible or haptic feedback. The method yet further includes acquiring imagery in the computing system in association with the first view, and detecting an anomalous feature of the acquired imagery. Finally, the method includes selecting a different view in the sequence as a substitute for a next one of the views in the sequence in response to having detected the anomalous feature, and further presenting different guidance in the display for the different view in lieu of guidance for the next one of the views.

Abstract: An ultrasound guidance dynamic mode switching method includes selecting a predetermined ultrasound diagnostic procedure in memory of an ultrasound diagnostic computing system and identifying an operating mode of the system for a first sequence of views stored in the memory as a workflow in correspondence to the selected procedure. The method additionally includes placing the system in the identified operating mode and acquiring imagery of a target organ in association with the views of the first sequence of the workflow. Finally, the method includes detecting in the acquired imagery, a feature of the target organ mapped to a different operating mode, and in response to the detection, displaying a recommendation in a display to change operating modes, placing the system into the different operating mode, and acquiring additional imagery of the target organ utilizing the system in association with a different sequence of additional views of a different workflow.

Abstract: A method for prescriptively guiding an operator of an ultrasound imaging probe includes acquiring a sequence of image clips of a target organ utilizing an ultrasound imaging probe, determining a particular view of the target organ expressed by the acquired image clips and assessing a quality of each of the acquired image clips in respect to the particular view. On condition that the assessed quality falls below a pre-determined satisfactory quality for the particular view, a prescriptive movement of the probe is computed that has been pre-determined to produce quality improvement of a subsequently acquired image clip of the target organ for the particular view. Then, responsive to determining that the prescriptive movement has been computed a threshold number of times in connection with the sequence, the prescriptive movement is displayed concurrently with a display of subsequently acquired image clips of the target organ.

Abstract: An automatic extraction of disease-specific features from Doppler images to help diagnose valvular diseases is provided. The method includes the steps of obtaining a raw Doppler image from a series of images of an echocardiogram, isolating a region of interest from the raw Doppler image, the region of interest including a Doppler image and an ECG signal, and depicting at least one heart cycle, determining a velocity envelope of the Doppler image in the region of interest, extracting the ECG signal to synchronize the ECG signal with the Doppler image over the at least one heart cycle, within the region of interest, calculating a value of a clinical feature based on the extracted ECG signal synchronized with the velocity envelope, and comparing the value of the clinical feature with clinical guidelines associated with the clinical feature to determine a diagnosis of a disease.

Abstract: An automatic extraction of disease-specific features from Doppler images to help diagnose valvular diseases is provided. The method includes the steps of obtaining a raw Doppler image from a series of images of an echocardiogram, isolating a region of interest from the raw Doppler image, the region of interest including a Doppler image and an ECG signal, and depicting at least one heart cycle, determining a velocity envelope of the Doppler image in the region of interest, extracting the ECG signal to synchronize the ECG signal with the Doppler age over the at least one heart cycle, within the region of interest, calculating a value of a clinical feature based on the extracted ECG signal synchronized with the velocity envelope, and comparing the value of the clinical feature with clinical guidelines associated with the clinical feature to determine a diagnosis of a disease.

Abstract: An automatic extraction of disease-specific features from Doppler images to help diagnose valvular diseases is provided. The method includes the steps of obtaining a raw Doppler image from a series of images of an echocardiogram, isolating a region of interest from the raw Doppler image, the region of interest including a Doppler image and an ECG signal, and depicting at least one heart cycle, determining a velocity envelope of the Doppler image in the region of interest, extracting the ECG signal to synchronize the ECG signal with the Doppler age over the at least one heart cycle, within the region of interest, calculating a value of a clinical feature based on the extracted ECG signal synchronized with the velocity envelope, and comparing the value of the clinical feature with clinical guidelines associated with the clinical feature to determine a diagnosis of a disease.